Network Analysis: A comparative Analysis of Centrality Measures for the Brain Subregions of two Populations of Prairie Voles

A graph oriented project for the generalization of the Erdos Number using dijkstra's Algorithm and Networkx.

Learning From Networks (LFN) project repository. "Learning From Networks" is a course of the master degree in "Computer Engineering" at the University of Padua, Italy.

The official repository for the source code of the article "Local graph embeddings based on neighbors degree frequency of nodes".

Calculate closeness centrality of graph using functional BFS

A repository for COSC-355 Network Science at Amherst College using Cytoscape and the Python package NetworkX

Sequential and parallel implementation of different Centrality Measures.

Closeness centrality approximation for undirected graphs with Eppstein-Wang algorithm

Implementing a Graph ADT to analyze social network data from GitHub and Facebook, focusing on metrics like influence, centrality, and proximity using algorithms such as Dijkstra's

We will get data about movies in between 1995 and 2004 from IMBD and we will perform a complete SNA

This project evolves around the concept of networks, centralities, and community detection, and infection simulation.

This project utilizes various metrics to analyze a graph network based on data of ENZYMES_g295

This project was created for Graph-Based Analysis for Big Data in Social Networks class at College of Staten Island (CUNY) in December 2020.

Network analysis using NetworkX library

Given an instance of set of nodes in a social network graph, the aim is to find the influencing important users and to predict the likelihood of a future association between two nodes, knowing that there is no association between the nodes in the current state of the graph.

A Closeness Centrality exercise in Scala

Exploratory Social Network Analysis using NetworkX. Predicting Review Rating using features derived from Network Properties.

Analysis of London street gang network

Demo on applying the concept of network analysis on a network of connected railway stations, attempting to identify the important stations (nodes) in this network. Web scraping techniques using rvest package is also briefly discussed upon.

Analysis of the traffic flow in the cities of Bristol and Cincinnati, considering data gathered by Uber Movement.